Cloud Native Machine Learning Systems at Day Two and Beyond
Offered By: CNCF [Cloud Native Computing Foundation] via YouTube
Course Description
Overview
Explore the challenges and solutions for cloud-native machine learning systems in this 26-minute conference talk from KubeCon + CloudNativeCon Europe 2021. Delve into the unique aspects of ML systems, including reproducibility, feature engineering, and explainability. Learn how to navigate pitfalls in interactive development, production monitoring, and DevOps practices for maturing cloud-native ML systems. Gain insights from industry experiences to address issues like GDPR compliance, high-velocity data science, and delivery challenges. Discover practical strategies for building robust, scalable ML infrastructures on Kubernetes, preparing you for day-two operations and beyond.
Syllabus
Introduction
Agenda
Machine Learning Systems
Hidden Technical Debt
Reproducibility
Feature Engineering
Library Stack
Explainability
GDPR
High Velocity Data Science
Delivery Challenges
Inputs Outputs
The Big Picture
Taught by
CNCF [Cloud Native Computing Foundation]
Related Courses
Building Geospatial Apps on Postgres, PostGIS, & Citus at Large ScaleMicrosoft via YouTube Unlocking the Power of ML for Your JavaScript Applications with TensorFlow.js
TensorFlow via YouTube Managing the Reactive World with RxJava - Jake Wharton
ChariotSolutions via YouTube What's New in Grails 2.0
ChariotSolutions via YouTube Performance Analysis of Apache Spark and Presto in Cloud Environments
Databricks via YouTube